Influence of nonideal voltage measurement on parameter estimation in permanent-magnet synchronous machines

This paper investigates the influence of nonideal voltage measurements on the parameter estimation of permanentmagnet synchronous machines (PMSMs). The influence of nonideal voltage measurements, such as the dc bus voltage drop, zero shift in the amplifier, and voltage source inverter nonlinearities, on the estimation of different machine parameters is investigated by theoretical and experimental analysis. For analysis, a model-reference-adaptive-system-based estimator is first described for the parameter estimation of the q-axis inductance, stator winding resistance, and rotor flux linkage. The estimator is then applied to a prototype surface-mounted PMSM to investigate the influence of nonideal voltage measurement on the estimation of various machine parameter values. It shows that, at low speed, the inverter nonlinearity compensation has significant influence on both the rotor flux linkage and winding resistance estimations while, at high speed, it has significant influence only on the winding resistance estimation and has negligible influence on the rotor flux linkage estimation. In addition, the inverter nonlinearity compensation will not influence the q-axis inductance estimation when it is under id = 0 control. However, the dc bus voltage drop due to the load variation and zero shift in the amplifier will significantly influence the q-axis inductance estimation. © 2011 IEEE

Multiobjective Optimization of PID Controller of PMSM

PID controller is used in most of the current-speed closed-loop control of permanent magnet synchronous motors (PMSM) servo system. However, Kp, Ki, and Kd of PID are difficult to tune due to the multiple objectives. In order to obtain the optimal PID parameters, we adopt a NSGA-II to optimize the PID parameters in this paper. According to the practical requirement, several objective functions are defined. NSGA-II can search the optimal parameters according to the objective functions with better robustness. This approach provides a more theoretical basis for the optimization of PID parameters than the aggregation function method. The simulation results indicate that the system is valid, and the NSGA-II can obtain the Pareto front of PID parameters

Parameter identification of variable flux reluctance machines excited by zero-sequence current accounting for inverter nonlinearity

To identify the parameters of variable flux reluctance machines (VFRMs), the input voltage value is usually obtained from the reference voltage indirectly. However, the reference and actual voltages may be different due to the nonlinearity of the open winding inverter when using zero-sequence current, leading to the inaccuracy of parameter identification. To solve this problem, this paper proposes an equivalent nonlinearity voltage error model of the open winding inverter to compensate for the input voltage of VFRM during the online parameter identification. Since in the proposed method the phase current direction is not required, the calculation time can be reduced. Moreover, in the developed parameter identification model of VFRM the derived equivalent nonlinear voltage error is used to correct the input of the identification model so as to improve the accuracy of parameters. Finally, the experimental results on the prototype VFRM are presented for verification

Parameter estimation for condition monitoring of PMSM stator winding and rotor permanent magnets

Winding resistance and rotor flux linkage are important to controller design and condition monitoring of a surface-mounted permanent-magnet synchronous machine (PMSM) system. In this paper, an online method for simultaneously estimating the winding resistance and rotor flux linkage of a PMSM is proposed, which is suitable for application under constant load torque. It is based on a proposed full-rank reference/variable model. Under constant load torque, a short pulse of id 0 is transiently injected into the d-axis current, and two sets of machine rotor speeds, currents, and voltages corresponding to id = 0 and id 0 are then measured for estimation. Since the torque is kept almost constant during the transient injection, owing to the moment of system inertia and negligible reluctance torque, the variation of rotor flux linkage due to injected id 0 can be taken into account by using the equation of constant torque without measuring the load torque and is then associated with the two sets of machine equations for simultaneously estimating the winding resistance and rotor flux linkage. Furthermore, the proposed method does not need the values of the $dq$-axis inductances, while the influence from the nonideal voltage measurement, which will cause an ill-conditioned problem in the estimation, has been taken into account and solved by error analysis. This method is finally verified on two prototype PMSMs and shows good performance. © 1982-2012 IEEE

GPU Implementation of DPSO-RE Algorithm for Parameters Identification of Surface PMSM Considering VSI Nonlinearity

In this paper, an accurate parameter estimation model of surface permanent magnet synchronous machines (SPMSMs) is established by taking into account voltage-source-inverter (VSI) nonlinearity. A fast dynamic particle swarm optimization (DPSO) algorithm combined with a receptor editing (RE) strategy is proposed to explore the optimal values of parameter estimations. This combination provides an accelerated implementation on graphics processing unit (GPU), and the proposed method is, therefore, referred to as G-DPSORE. In G-DPSO-RE, a dynamic labor division strategy is incorporated into the swarms according to the designed evolutionary factor during the evolution process. Two novel modifications of the movement equation are designed to update the velocity of particles. Moreover, a chaotic-logistic-based immune RE operator is developed to facilitate the global best individual (gBest particle) to explore a potentially better region. Furthermore, a GPU parallel acceleration technique is utilized to speed up parameter estimation procedure. It has been demonstrated that the proposed method is effective for simultaneous estimation of the PMSM parameters and the disturbance voltage (Vdead) due to VSI nonlinearity from experimental data for currents and rotor speed measured with inexpensive equipment. The influence of the VSI nonlinearity on the accuracy of parameter estimation is analyzed

Adaptive ac filter parameters identification for voltage-oriented control of three-phase voltage-source rectifiers

This paper proposes an adaptive voltage-oriented control (VOC) with online ac filter parameters identification for three-phase voltage-source rectifier (VSR). A new method based on adaptive linear neuron (ADALINE) is first designed to identify the ac filter parameters. For accurate identification, the VSR nonlinearity is included in the ADALINE structure. Thereafter, the developed ADALINE is inserted in the VOC to realise an adaptive VOC. Thus, the decoupled terms and the proportional-integral current controller gains are updated online. Finally, the ADALINE ability to track properly the ac filter parameters is investigated by experimental analysis. It shows that the VSR nonlinearity consideration has significant influence on the resistance identification. Compared to the VOC, the enhancement of the proposed adaptive VOC is experimentally proved. The originality of this paper is the building of a VSR model including VSR nonlinearity that is suitable for implementation with ADALINE. This leads to ease of implementation and accurate identification